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Delegates are invited to meet and discuss with the poster presenters during the poster presentation sessions between 10:30-11:30 and 16:00-17:00 on Thursday, 19 November 2015.

Lead Session Chair:
Stephan Barth, ForWind - Center for Wind Energy Research, Germany
Matthew Cand Hoare Lea Acoustics, United Kingdom
Co-authors:
Matthew Cand (1) F Mark Jiggins (1)
(1) Hoare Lea Acoustics, Bristol, United Kingdom

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Presenter's biography

Biographies are supplied directly by presenters at EWEA 2015 and are published here unedited

Matthew is an Executive Engineer with Hoare Lea Acoustics. Matthew graduated from the Ecole Polytechnique in France, and also holds a Doctor of Philosophy degree in Mechanical Engineering, awarded by Imperial College London. Matthew has been involved at different stages, from inception to completion, on a wide variety of wind farm projects throughout the UK. Matthew has provided expert witness evidence at several wind farm planning hearings and inquiries. Matthew is a member of the UK Institute of Acoustics and joined their working group which produced the Good Practice Guide on the assessment of wind turbine noise.


Poster


Poster Award Winner Poster Download poster (10.87 MB)

Abstract

Undertaking automated wind farm noise feature analysis directly on a live measurement system

Introduction

The measurement of noise at typical residential neighbours to wind farms offers challenges not ordinarily found in other environmental noise measurements. These include the need to measure noise levels which are relatively low, often comparable to the residual noise in the absence of the turbines, and under windy conditions. Furthermore, the variability of noise levels is crucially dependent on the changes in the weather conditions. The requirement to establish these dependencies means that noise measurements often extend over periods of months. Finally, the measurements are frequently undertaken in remote rural locations which can prove difficult or time-consuming to access. Yet noise forms one of the impacts of a windfarm which requires attention, and the focus has increasingly shifted towards specific features of the noise, which may depend on a complex interaction of operational factors at some sites.

The noise monitoring process ordinarily requires the deployment of a logging system followed by regular site visits to manually download data. The downloaded noise data is then analysed against separately acquired operational/meteorological data from the wind farm. The need to manually download noise data is driven by size of the audio data required for subsequent acoustic feature analysis, which precludes its transmission via remote networks. Furthermore, the analysis of noise features has usually required lengthy post-processing analysis by office-based specialists.

Approach

This paper will demonstrate a novel remote noise monitoring and analysis system which has been designed to overcome the limitations of such traditional systems. Instead of undertaking the analysis back in the office using manually downloaded data, the "smart" sound level analysis systems developed undertake the analysis directly at the site.

The design philosophy is believed to be unique, as the objective analysis of acoustic features, including for example tones and amplitude modulation, is implemented at the remote monitoring station, thereby greatly reducing the onward data transmission requirements. This allows the “live” transmission of this information through for example mobile phone networks, allowing a rapid evaluation of these features, and of current noise levels. This can be linked to operational/meteorological data, providing almost real time feedback on noise in terms of both overall levels and features to involved parties.

Main body of abstract

This system has been successfully developed and installed by Hoare Lea Acoustics, providing ongoing live data. The architecture, components and operation of the system will be described. Examples of the capabilities and outputs of such a system will be shown, and the possibilities this offers in terms of operational feedback in relation to far-field noise impacts.


Conclusion

The system developed allows for more efficient and cost-effective analysis of wind turbine noise in practical situations. It also allows this information to be fed back directly to the site operator in order to modify the site operation promptly if required: this reduces delays and associated impacts on wind farm neighbours.


Learning objectives
The relevance of noise levels and features as an environmental impact will first be explained as background to the capabilities of the system presented. This presentation will then demonstrate what represent the cutting edge in terms of noise measurements, to best represent what is often a complex picture at operating wind farm sites, and offer rapid and useful information to operators.